Factors associated with HIV RNA viral non-suppression among children and adolescents with HIV attending public health facilities in Gulu City,Uganda: a retrospective cohort study

Abstract

Background:

Human immunodeficiency virus (HIV) RNA viral load testing is the gold standard for monitoring antiretroviral therapy (ART), and sustained viral suppression is critical for preventing HIV-related morbidity and transmission. However, children and adolescents with HIV (CAWH) often experience lower viral suppression rates than adults. Data on the incidence of HIV RNA viral non-suppression and its determinants among CAWH in northern Uganda remain limited.

Objectives:

To determine the incidence and factors associated with HIV RNA viral load non-suppression among CAWH receiving ART in Gulu City, Uganda.

Design:

Retrospective cohort study.

Methods:

We reviewed records of CAWH receiving ART at public health facilities in Gulu City. Data were abstracted for HIV RNA viral load outcomes at 6, 12, 18, and 24 months and at the most recent follow-up. The primary outcome was HIV RNA viral non-suppression during follow-up. Bivariable and multivariable Cox proportional hazards regression models were used to identify factors associated with viral load non-suppression. Adjusted hazard ratios (aHRs) with 95% confidence intervals (CIs) were reported.

Results:

Among 218 participants, the median age was 12.5 years (interquartile range (IQR), 7–18), and 153 (70.2%) were female. During follow-up, 99 participants (45.4%) experienced viral load non-suppression. The incidence rate of viral load non-suppression was 25.6 cases per 100 person-years. Factors independently associated with non-suppression included age <5 years (aHR: 2.59, 95% CI: 1.30–5.17), poor ART adherence (aHR: 1.96, 95% CI: 1.21–3.17), non-disclosure of HIV status (aHR: 2.19, 95% CI: 1.27–3.80), advanced WHO clinical stage (III–IV) at presentation (aHR: 3.07, 95% CI: 1.41–6.69), and economic hardship (aHR: 2.13, 95% CI: 1.32–3.42).

Conclusion:

Viral load non-suppression among CAWH in Gulu City was high, with the majority experiencing viral non-suppression by approximately 6 months after ART initiation. Strengthening adherence support, early disclosure of HIV status, and targeted interventions for younger children and socioeconomically vulnerable households may improve viral suppression outcomes in this population.

Plain language summary

Why some children and adolescents living with HIV in Gulu City, Uganda, do not achieve viral suppression

Why was the study done?

The researchers wanted to find out why many children and adolescents living with HIV in Gulu City, Uganda, do not achieve or maintain viral suppression, that is maintaining their viral load at low level. Viral suppression is important because it helps people stay healthy and reduces the chance of transmitting the virus. Children and adolescents often face unique challenges, such as difficulty taking medicines regularly or not knowing their HIV status.

How was the study done?

The team reviewed medical records of 218 children and adolescents receiving HIV care at public health facilities in Gulu City. They collected information on each person’s HIV viral load results, age, treatment adherence, stage of HIV illness, disclosure status, and family economic situation. They used statistical analysis to find which factors were linked to poor viral control.

What did the study find?

Nearly half (45%) of the young people did not achieve or maintain viral suppression. Those under five years old, those who missed taking their medicines, those who had not been told about their HIV status, those with advanced HIV disease, and those from families facing economic hardship were more likely to have poor viral control.

What do the findings mean?

These findings show that medical treatment alone is not enough to help young people living with HIV achieve viral suppression. Stronger support is needed, especially counselling, early disclosure, and help for families facing economic difficulties, to improve adherence and health outcomes. HIV care programs for children and adolescents should combine medical treatment with social and emotional support to help every young person live a healthy, fulfilling life.

Keywords

ART children and adolescents HIV non-suppression Uganda viral load

Introduction

Globally, approximately 40 million people were estimated to be living with human immunodeficiency virus (HIV) in 2024, two-thirds are from the African region.¹ Eastern and Southern Africa are the most affected regions with over 20 million people affected, which contributes to about 54% of all people living with HIV in the world.¹ In December 2020, the Joint United Nations Programs on HIV/AIDS (UNAIDS) released a set of ambitious targets calling for 95% of all people with HIV to know their HIV status, 95% of all people with diagnosed HIV infection to receive sustained antiretroviral therapy, and 95% of all people receiving antiretroviral therapy to have viral suppression by 2025.²

Periodic viral load testing is “the gold standard” for HIV, the most accurate way to determining whether antiretroviral therapy (ART) is suppressing HIV viral replication.³ Achieving viral suppression protects the body’s immune system, helps people with HIV stay healthy, and prevents transmission of HIV to other people.⁴ However, a non-suppressed viral load suggests treatment provision needs attention, including offering adherence support such as community-based adherence support services.³ Children and adolescents with HIV (CAWH) who are newly initiated on ART should have a viral load test done at month 6 and month 12 and every 6 months thereafter.³ Globally, the proportion of children and adolescents with viral suppression was 78%, 72%, and 65% at one, 2 and 3-years, respectively, after ART initiation.⁵ A multicenter study among children on second line ART found pooled viral suppression amongst children in low- and middle-income countries (LMICs) after 6 months on first line ART initiation to be 62.2% in the early, 74.3% in the intermediate and 80.9% in the late study period.^6,7

In Uganda, HIV viral load testing and viral suppression rates among CAWH remain suboptimal despite improvements in viral load coverage, with over 30% of adolescents having no access to a viral load test in 2017.⁸ Unfortunately, viral suppression rates did not reach 75% for adolescents who had a viral load test done; far below the target of 95%.⁸ Previous studies have also reported low viral load suppression among children and adolescents in Uganda.⁹ This is especially concerning in Gulu City, Northern Uganda, a post-conflict region (1986–2006), due to its high incidence of HIV among children and adolescents.¹⁰

Studies have revealed several factors associated with viral non-suppression among CAWH, including age, male gender, education level, duration on ART therapy, WHO clinical stage being on second line ART regimen and presence of comorbidities, treatment failures, and repeat testing after suspected failure.^9,11–13 However, data on the proportion and factors associated with HIV RNA viral non-suppression amongst CAWH is still low in our setting in Northern Uganda.

Despite receiving ART, CAWH across the globe experience substantial AIDS-related morbidity and mortality.¹⁴ HIV associated mortality was the eighth leading cause of adolescent death globally and the fourth leading cause in LMICs.¹⁵ This high mortality rate may be partly due to low levels of ART adherence that are associated with viral non-suppression. In Uganda, there are about 95,000 CAWH with approximately 60% on ART who have viral non-suppression compared to adults.¹⁶ This falls short of the expected 95% UNAIDS target.¹⁷ Compared to adult clients in care, viral non-suppression is much higher among CAWH.¹⁸ Establishing viral non-suppression among adolescents is critical for timely detection of treatment failures.¹² We determined the incidence and factors associated with HIV RNA viral non-suppression among CAWH attending care at public health facilities in Gulu City, Northern Uganda.

Methods

Study design

A retrospective cohort study. Anonymized records of CAWH receiving ART from January 2018 to September 2022 were reviewed to establish the incidence of viral non-suppression and associated factors. The participants were followed from the date of ART initiation until loss to follow up or administrative censoring. Data were abstracted between May and July 2024. We followed the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines (Supplemental Material).¹⁹

Study setting

This study was conducted at all public health facilities offering comprehensive HIV prevention, care, and treatment services in Gulu City, Northern Uganda. The selected facilities include Gulu Regional Referral Hospital, Aywee Health Centre III(HCIII), Bardege HCIII, Laroo HCIII, Layibi Techo HCIII, and Gulu Police HCIII. Within the study period, Gulu RRH, Aywee HCIII, Bardege HCIII, Layibi Techo HCIII, Laroo HCIII, Gulu Polic HCIII enrolled into care approximately 159, 24, 36, 21, 20, and 12 children and adolescents, respectively. Gulu Regional Referral Hospital is a high-volume health facility and a referral point with an ART clinic that is fully operational weekly from Monday to Friday, with Tuesday as a special clinic day for children and adolescents. The other public health facilities operate ART clinic on selected days in the week. There are dedicated health workers such as medical officers, clinical officers, nurses, laboratory technicians, counsellors, and community health workers among others. Most of the health workers attached to these clinics have received comprehensive training in HIV RNA Viral load monitoring. According to the consolidated guidelines for the prevention and treatment of HIV and AIDS in Uganda,²⁰ viral load monitoring for children and adolescents aged 0–19 years is recommended to be done at 6 and 12 months after initiating ART; and if viral suppression is reached, every 6 months thereafter. If not suppressed, an algorithm is followed thereafter based on the outcome of intensive adherence counselling (IAC) sessions with a maximum of six IAC sessions to be conducted.

Study population

The study population comprised records of CAWH aged 0–19 years who were receiving comprehensive HIV care and treatment at public health facilities in Gulu City, Uganda. Participants included those enrolled in care between January 2018 and September 2022 and followed up until September 2024 or until administrative censoring. Eligible participants were treatment-naïve children and adolescents initiated on first-line ART with at least 6 months of treatment follow-up. Records were excluded if viral load data were missing or if more than 75% of the predefined variables in the data abstraction tool were incomplete. CAWH transferred into the participating facilities from other health facilities were also excluded.

Sample size estimation

Sample size was estimated using Cochran’s Modified Formula for Finite Populations

n = \frac{n_{0}}{1 + \frac{n 0 - 1}{N}}

Where; n₀: Cochran’s sample size computed using the formula for ideal sample size

N: the size of the population

n = \frac{385}{1 + \frac{385 - 1}{503}}

n = 218 participants

A total of 218 participants were enrolled from different facilities as follows: Gulu Regional Referral Hospital (62.4%, n = 136), Aywee HC3 (7.8%, n = 17), Bardege HC3 (14.7%, n = 32), Laroo HC3 (5.5%, n = 12), Layibi Techo HC3 (6.9%, n = 15), and Gulu Police HC3 (2.8%, n = 6) (Figure 1).

Figure 1.

Enrolment flow chart of the study participants.

Sampling

Consecutive sampling was used. Eligible participants were identified from the Electronic Medical Records (EMR) system and/or ART registers and enrolled sequentially until the required sample size for each participating facility was achieved.

Data abstraction

Data were abstracted using a structured data abstraction tool by trained research assistants in collaboration with ART clinic staff at the participating facilities. Information was obtained from client treatment files, pre-ART and ART registers, and electronic medical records.

Study variables

Dependent variable

The primary outcome was viral load non-suppression, defined as an HIV RNA viral load ⩾1000 copies/mL of blood.

Independent variables

Sociodemographic factors

Age, sex, education status, district of residence, relationship of treatment supporter to the client, point of entry into HIV care, HIV status disclosure, and psychosocial factors. These variables were obtained from the ART client care card, which routinely captures sociodemographic information, treatment supporter details, and psychosocial support information documented in the psychosocial support (PSS) section.

Clinical factors

Baseline CD4 count, baseline WHO clinical stage, baseline tuberculosis (TB) status, ART-related side effects, hepatitis B status, differentiated service delivery (DSD) model approach, ART regimen line, and current ART regimen.

Operational definitions

Differentiated Service Delivery model. DSD model refers to a patient-centered approach to HIV care in which ART services are tailored according to the clinical stability and needs of the patient to improve treatment outcomes and reduce the burden on health systems. In Uganda, common DSD models include facility-based individual management, fast-track ART refills, community drug distribution points, and multimonth ART dispensing for clinically stable patients.

Disclosure of HIV status. Disclosure status referred to whether a child or adolescent had been informed of their HIV diagnosis by a caregiver or healthcare provider at the time of assessment. Participants were classified as disclosed if they were aware of their HIV status and non-disclosed if the diagnosis had not been revealed to them.

WHO clinical staging. WHO clinical staging was used to classify HIV disease severity at presentation according to the World Health Organization staging system (Stages I–IV). Stage I represents asymptomatic infection or mild disease. Stage II includes mild clinical manifestations such as recurrent upper respiratory infections and minor mucocutaneous conditions. Stage III represents advanced disease, including chronic diarrhea, persistent fever, severe bacterial infections, and pulmonary tuberculosis. Stage IV represents severe disease with AIDS-defining conditions such as opportunistic infections and severe wasting.

Data management

Data collected were captured electronically into Kobo Toolbox (Cambridge, MA, USA), a secure (password encrypted), open-source software developed for humanitarian and research data collection. Daily, the principal investigator checked the data for completeness. Data were downloaded from Kobo Toolbox in an Excel format for preliminary preview.

Data analysis

A cleaned dataset was imported into Stata version 18.0 (StataCorp LLC, College Station, Texas, USA) for cleaning and analysis. Descriptive statistics summarized baseline characteristics: categorical variables as frequencies and percentages, and continuous variables as means (±standard deviation) or medians (interquartile range, IQR) as appropriate. Incidence of viral non-suppression was computed as cases of viral load non-suppression per 100 person-years. Time-to-event analysis measured the interval from ART initiation to the first documented non-suppressed viral load. Bivariable and multivariable Cox proportional hazards regression assessed associations between covariates and viral load non-suppression. Variables with p < 0.20 in bivariable analysis entered the multivariable model, adjusting for confounders such as disclosure status and psychosocial factors. Associations were reported as hazard ratios (HR) with 95% confidence intervals (CIs) and p-values.

Time to viral non-suppression was computed from the date of ART initiation to the time the event occurred (first viral load non-suppression). Bivariable and multivariable Cox proportional hazards models were used to assess the association between viral load non-suppression and participant characteristics. Variables with a p-value less than 0.2 at bivariable analysis were included in the final multivariable model. We adjusted for potential confounders including disclosure status and psychosocial factors. Adjusted HR (aHR) with 95% CI and p-value were used to assess the strength of association and statistical significance.

Ethical considerations

Ethical approval and a waiver of informed consent were obtained from Gulu University Research and Ethics committee (GUREC 2023-633). Prior to data abstraction, administrative clearance was obtained from Gulu City Health Officer and Gulu Regional Referral Hospital Research and Ethics committee as well as facility In-charges. Confidentiality of the participants’ information was maintained by using only de-identified data.

Results

Sociodemographic characteristics of the participants

A total of 218 participants records were included in the analysis. The median age of participants was 12.5 years (IQR: 7–18 years). Majority (70.2%) of the study participants were female and 158 (72.5%) reported mother as their treatment supporter. Among those aged 5–19 years, 139 (70.9%) were in school. HIV status disclosure was documented in 75.7% of participants. Economic hardship (28.9%) and food insecurity (26.1%) were the most common psychosocial challenges (Table 1).

Table 1.

Sociodemographic characteristics of the participants (N = 218).

Characteristic (n = 218)	Frequency (n)	Percentage (%)
Age in years; median (interquartile range)	12.5 (7–18)
<5	22	10.1
5–9	60	27.5
10–19	136	62.4
Sex
Female	153	70.2
Male	65	29.8
In school (5–19 years)
Yes	139	70.9
No	57	29.1
District
Gulu City	175	80.3
Omoro	15	6.9
Nwoya	4	1.8
Gulu district	19	8.7
Other^a	5	2.3
Relationship of treatment supporter to index client
Mother	158	72.5
Father	19	8.7
Grand parent	10	4.6
Sibling	6	2.8
Other^b	25	11.5
Care entry point
Outpatient department	84	38.5
Antiretroviral therapy clinic	75	34.4
Maternal and child health clinic	41	18.8
Community	2	0.9
Other^c	16	7.3
Disclosure status
Yes	165	75.7
No	53	24.3
Psychosocial factors
Economic challenges	63	28.9
Food insecurity	5	26.1
Anger	11	5.0
Fear	9	4.1
Stigma	8	3.7
Stress	8	3.7
Dysfunctional family	9	4.1
Others^d	18	8.3

Amuru, Masindi, Pader, Omoro.

Aunt, friend, husband, spouse, boyfriend, stepmother, mother-in-law, wife, Watoto church.

Acute care clinic, Adolescents clinic, Inpatient department, Nutrition, Outreach.

Non-disclosure, pill burden, denial, spiritual issues, long distances.

Clinical characteristics of the participants

At baseline ART initiation, most participants (86.2%, n = 188) were in WHO clinical stage I and under Facility Based Individual Management (FBIM) approach (77.1%, n = 168) under the DSD model. Baseline median CD4 cell count of the participants was 365 cells/µL (IQR: 200–641). Fifty-three participants (24.3%) had not been disclosed to their HIV status. Regarding psychosocial factors, (28.9%, n = 63) had economic challenges and (26.1%, n = 57) faced food insecurity. During the follow-up period, 47 participants were transferred out, 12 dropped and 19 lost to follow-up. Details are in Table 2.

Table 2.

Clinical characteristics of the participants.

Characteristic	At baseline, n = 218, n (%)	At 6 months, n = 218, n (%)	At 12 months, n = 197, n (%)	At 18 months, n = 181, n (%)	At 24 months, n = 166, n (%)	Current, n = 152, n (%)
WHO clinical staging
I	188 (86.2)	188 (95.4)	177 (97.8)	160 (96.4)	149 (98.6)	139 (99.3)
II	16 (7.3)	5 (2.5)	3 (1.6)	4 (2.4)	1 (0.7)	0 (0.0)
III	12 (5.5)	4 (2.0)	1 (0.6)	2 (1.2)	1 (0.7)	1 (0.7)
VI	2 (0.9)	0 (0.0)	0 (0.0)	0 (0.0)	0 (0.0)	0 (0.0)
TB status
Yes	5 (2.3)	6 (3.2)	2 (1.1)	2 (1.2)	2 (0.7)	1 (0.7)
No	206 (94.5)	190 (95.9)	179 (98.9)	164 (98.8)	150 (99.3)	139 (99.3)
Presumed	7 (3.2)	1 (0.5)	0 (0.0)	0 (0.0)	0 (0.0)	0 (0.0)
Advanced HIV disease status
No	186 (85.3)	189 (95.9)	176 (97.2)	162 (97.6)	149 (98.7)	138 (98.6)
Yes	32 (14.7)	8 (4.1)	5 (2.8)	4 (2.4)	2 (1.3)	2 (1.4)
Side effects of antiretroviral therapy at baseline
Yes	1 (0.5)	1 (0.5)	1 (0.6)	0 (0.0)	1 (0.7)	1 (0.8)
No	196 (99.5)	196 (99.5)	175 (99.4)	160 (100.0)	144 (99.3)	130 (99.2)
Hepatitis B status
Yes	1 (0.5)	0 (0.0)	0 (0.0)	0 (0.0)	0 (0.0)	0 (0.0)
No	7 (3.2)	9 (4.5)	11 (6.1)	11 (6.6)	13 (8.6)	10 (7.1)
Unknown	210 (96.3)	188 (95.4)	170 (93.9)	155 (93.4)	138 (91.4)	130 (92.9)
DSDM Approach
FBIM	168 (77.1)	152 (77.1)	125 (69.1)	100 (60.2)	95 (62.9)	87 (62.1)
FTDR	2 (0.9)	7 (3.6)	15 (8.3)	21 (12.7)	18 (11.9)	26 (18.6)
FBG	48 (22.0)	38 (19.3)	40 (22.1)	39 (23.5)	30 (19.9)	17 (12.1)
CDDP	0 (0.0)	0 (0.0)	1 (0.5)	4 (2.4)	6 (4.0)	9 (6.4)
CCLAD	0 (0.0)	0 (0.0)	0 (0.0)	2 (1.2)	2 (1.3)	1 (0.7)
Client status
Active	218 (100.0)	197 (90.4)	181 (91.9)	166 (91.7)	151 (91.0)	140 (92.1)
Missed	0 (0.0)	0 (0.0)	1 (0.5)	0 (0.0)	0 (0.0)	0 (0.0)
Loss to follow-up	0 (0.0)	6 (2.8)	4 (2.0)	2 (1.1)	5 (3.0)	2 (1.3)
Dropped	0 (0.0)	1 (0.5)	3 (1.5)	1 (0.6)	4 (2.4)	3 (2.0)
Transferred out	0 (0.0)	14 (6.4)	8 (4.1)	12 (6.6)	6 (3.6)	7 (4.6)
ART regimen
TDF/3TC/DTG	47 (23.9)	63 (28.9)	69 (39.2)	66 (41.2)	67 (46.2)	63 (48.1)
ABC/3TC/DTG	27 (13.7)	44 (20.2)	41 (23.3)	47 (29.4)	56 (38.6)	67 (51.1)
ABC/3TC/LPVr	52 (26.4)	51 (23.4)	40 (22.7)	32 (20.0)	20 (13.8)	0 (0.0)
AZT/3TC/LPVr	2 (1.0)	2 (0.9)	1 (0.6)	2 (1.2)	0 (0.0)	0 (0.0)
TDF/3TC/ATVr	1 (0.5)	1 (0.5)	0 (0.0)	0 (0.0)	0 (0.0)	0 (0.0)
ABC/3TC/ATVr	0 (0.0)	1 (0.5)	0 (0.0)	0 (0.0)	0 (0.0)	0 (0.0)
TDF/3TC/LPVr	0 (0.0)	0 (0.0)	0 (0.0)	0 (0.0)	1 (0.7)	0 (0.0)
Other	68 (34.5)	56 (25.7)	25 (14.2)	13 (8.1)	1 (0.7)	1 (0.8)
Regimen Line
First line	218 (100.0)	196 (99.5)	180 (99.5)	166 (100.0)	151 (100.0)	139 (99.3)
Second line	0 (0.0)	1 (0.5)	1 (0.5)	0 (0.0)	0 (0.0)	1 (0.7)
CD4testresult	N = 65	N = 20	N = 15	N = 12	N = 14	N = 5
Median (IQR)	365 (200–641)	828 (534.5–996)	791 (640–1286)	706 (382.5–952.5)	888 (601–1053)	607 (555–860)
<200	6 (9.2)	0 (0.0)	0 (0.0)	2 (16.7)	1 (7.1)	1 (20.0)
>200	59 (90.8)	20 (100.0)	15 (100.0)	10 (83.3)	13 (92.9)	4 (80.0)
Adherence
>95% (Good)	N/A	169 (85.8)	153 (84.5)	139 (83.7)	133 (88.1)
<95%–85% (Fair)		18 (9.1)	23 (12.7)	21 (12.7)	11 (7.3)
<85%(Poor)		10 (5.1)	5 (2.7)	6 (3.6)	7 (4.6)
Evidence of IAC
Yes	0 (0.0)	41 (20.8)	38 (21.0)	23 (13.9)	27 (17.8)	22 (15.7)
No	0 (0.0)	8 (4.1)	8 (4.4)	6 (3.6)	7 (4.6)	11 (7.9)
N/A	218 (100.0)	148 (75.1)	135 (74.6)	137 (82.5)	117 (77.5)	107 (76.4)

3TC, Lamivudine; ABC, Abacavir; ART, Antiretroviral therapy; ATVr, Atazanavir/ritonavir; CCLAD, Community Client-Led ART Delivery; CDDP, Community Drug Distribution Point; DSDM, Differentiated Service Delivery Model; DTG, Dolutegravir; FBG, Facility-Based Group; FBIM, Facility-Based Individual Management; FTDR, Fast-Track Drug Refill; IAC, Intensive Adherence Counselling; IQR, Interquartile range.; LPVr, Lopinavir/ritonavir; TB, Tuberculosis; TDF, Tenofovir disoproxil fumarate.

HIV viral non-suppression among children and adolescents on ART in Northern Uganda

Two hundred eighteen participants were followed up, the median follow-up time was 2.46 (0.98–2.46) years, and the total person-time observation was 387.4 person-years. During the study period, 45.4% (n = 99) had a non-suppressed viral load. At 6 months, viral load non-suppression was 22.9%, decreased to 14.4% at 18 months, increased to 19.3% at 24 months, and then dropped to 15.1% at the latest follow-up (Figure 2). The overall incidence rate of HIV viral non-suppression was 25.6 per 100 person years after ART treatment initiation (Figure 3).

Figure 2.

Trends in HIV viral load non-suppression.

Figure 3.

Time to viral non-suppression.

Bivariable analysis of factors associated with HIV viral non-suppression among children and adolescents on ART in Northern Uganda

At bivariable analysis, Age < 5 years (Crude hazard ratio (cHR): 2.44; 95% CI: 1.29–4.62), poor adherence to ART (cHR: 2.32; 95% CI: 1.40–3.83), non-disclosure (cHR: 2.25; 95% CI: 1.47–3.45) having economic challenges (cHR: 1.60; 95% CI: 1.04–2.45) were associated with HIV viral non-suppression (Table 3).

Table 3.

Bivariable analysis of factors associated with HIV viral non-suppression among children and adolescents on ART in Northern Uganda.

Variable	Suppressed viral load	Non suppressed viral load	Crude hazard ratio (95% CI)	p-Value
N	119 (54.6%)	99 (45.4%)
Age in years
<5	9 (7.6%)	13 (13.1%)	2.44 (1.29–4.62)	0.006
5–9	22 (18.5%)	38 (38.4%)	1
10–19	88 (73.9%)	48 (48.5%)	0.76 (0.49–1.16)	0.199
Sex
Female	83 (69.7%)	70 (70.7%)	1
Male	36 (30.3%)	29 (29.3%)	0.80 (0.52–1.24)	0.327
Care entry point
Outpatient Department	45 (37.8%)	39 (39.4%)	1
Antiretroviral therapy clinic	45 (37.8%)	30 (30.3%)	0.83 (0.52–1.34)	0.448
Maternal and child health clinic	18 (15.1%)	23 (23.2%)	1.00 (0.59–1.69)	0.997
Community	1 (0.8%)	1 (1.0%)	0.77 (0.11–5.63)	0.798
Other	10 (8.4%)	6 (6.1%)	0.89 (0.38–2.11)	0.795
DSDM Approach
FBIM	94 (79.0%)	74 (74.7%)	1
FTDR	1 (0.8%)	1 (1.0%)	1.39 (0.19–10.05)	0.746
FBG	24 (20.2%)	24 (24.2%)	0.75 (0.47–1.19)	0.232
Poor adherence to ART
No	111 (93.3%)	79 (79.8%)	1
Yes	8 (6.7%)	20 (20.2%)	2.32 (1.40–3.83)	0.001
Disclosure status
Yes	99 (83.2%)	66 (66.7%)	1
No	20 (16.8%)	33 (33.3%)	2.25 (1.47–3.45)	<0.001
⩾3 Missed appointments
No	34 (28.6%)	15 (15.2%)	1
Yes	85 (71.4%)	84 (84.8%)	1.29 (0.75–2.26)	0.355
Relationship of treatment supporter
Parent	86 (72.3%)	72 (72.7%)	1
Other	33 (27.7%)	27 (27.3%)	0.98 (0.62–1.54)	0.915
WHO clinical staging at baseline
I and II	113 (95.0%)	91 (91.9%)	1
III and IV	6 (5.0%)	8 (8.1%)	2.04 (0.98–4.21)	0.055
Psychosocial factors
Economic challenges	31 (26.1%)	32 (32.3%)	1.60 (1.04–2.45)	0.032
Food insecurity	26 (21.8%)	31 (31.3%)	1.12 (0.73–1.72)	0.596
Anger	5 (4.2%)	6 (6.1%)	2.12 (0.92–4.87)	0.076
Fear	3 (2.5%)	6 (6.1%)	2.03 (0.88–4.65)	0.095
Dysfunctional family	1 (0.8%)	8 (8.1%)	1.51 (0.73–3.11)	0.268
Stress	5 (4.2%)	3 (3.0%)	0.39 (0.12–1.27)	0.117
Stigma/discrimination	6 (5.0%)	2 (2.0%)	0.64 (0.16–2.61)	0.534

ART, Antiretroviral therapy; cHR, crude hazard ratio; CI, confidence interval; DSDM, Differentiated Service Delivery Model; FBG, Facility-Based Group; FBIM, Facility-Based Individual Management; FTDR, Fast-Track Drug Refill.

Multivariable analysis of factors associated with HIV viral non-suppression among children and adolescents on ART in Northern Uganda

At multivariable analysis, children aged below 5 years had 2.59 times higher hazards of HIV viral non-suppression as compared to those aged 5–9 years (aHR: 2.59; 95% CI: 1.30–5.17). Children with poor adherence to ART had 1.96 times higher hazards of HIV viral non-suppression as compared to those with good adherence to ART (aHR: 1.96; 95% CI: 1.21–3.17). Non-disclosure was associated with 2.19 times higher hazards of HIV viral non-suppression as compared to HIV status disclosure (aHR: 2.19; 95% CI: 1.27–3.80). Late WHO clinical stage (aHR: 3.07; 95% CI: 1.41–6.69) and having economic challenges (aHR: 2.13; 95% CI: 1.32–3.42) were also associated with higher hazards of HIV viral non-suppression (Table 4).

Table 4.

Multivariable analysis of factors associated with HIV viral non-suppression among children and adolescents on ART in Northern Uganda.

Variable	Adjusted hazard ratio (95% CI)	p-Value
Age in years
<5	2.59 (1.30–5.17)	0.007*
5–9	1
10–19	0.89 (0.55–1.45)	0.653
Poor adherence to ART
No	1
Yes	1.96 (1.21–3.17)	0.006*
Disclosure status
Yes	1
No	2.19 (1.27–3.80)	0.005*
WHO clinical staging at baseline
I and II	1
III and IV	3.07 (1.41–6.69)	0.005*
Psychosocial factors
Economic challenges	2.13 (1.32–3.42)	0.002*
Anger	1.58 (0.54–4.63)	0.401
Fear	1.65 (0.59–4.61)	0.336
Stress	0.64 (0.18–2.20)	0.475

aHR, adjusted hazard ratio; CI, confidence interval.

p < 0.05.

Discussion

This study assessed the incidence of HIV RNA viral non-suppression and its predictors among CAWH in Northern Uganda. The overall incidence rate of HIV RNA viral non-suppression was 25.6 cases per 100 person-years. There was a decrease in viral load non-suppression from 22.9% at 6 months to 14.4% at 18 months, then a rise to 19.3% at 24 months followed by a drop to 15.1% at the latest follow-up. Age less than 5 years, poor adherence to ART, HIV status non-disclosure, advanced WHO clinical stage (III and IV) and having economic challenges were associated with HIV viral non-suppression.

This study revealed a high incidence rate of HIV viral non-suppression (25.6 per 100 person-years) among children and adolescents, with 45.4% of the participants having a non-suppressed viral load during the follow-up period. This finding is higher than the pooled cumulative incidence in a multicenter analysis, which was 6.2 per person-years for sub-Saharan Africa.⁶ It is also higher than the 3.9 per 100 person-years reported in a study done in Uganda.¹⁶ This difference in incidence rate could be attributed to the fact that these studies considered two high viral load counts >1000 copies/mL while this study considered at least one high viral load counts >1000 copies/mL.

Regarding the trends of HIV viral non-suppression, while some improvement occurred over time, a significant proportion of participants continue to struggle with achieving viral suppression. Consistent with our finding of 45.4% viral non-suppression, Simms et al. reported 35% virological non-suppression among adolescents in Zimbabwe, particularly those with mental health symptoms. Similarly, Umar et al. found 39% non-suppression among adolescents and young people in Southern Malawi. Desta et al. reported 26.4% viral non-suppression in Northern Ethiopia, lower than our findings, possibly due to differences in healthcare system structures.^21–23 This highlights the need for interventions aimed at improving adherence and support systems for children and adolescents.

In this study, the hazard of HIV viral non-suppression was almost 3-folds higher more among children aged less than 5 years than those aged 5–9 years. Similar findings have been reported in studies done in Uganda and Tanzania.^9,24 Children under 5 years often face difficulty in swallowing ART formulations due to poor palatability, and pill burden.²⁵ Pediatric HIV-programs could explore the possibility of manufacturing child-friendly ART, palatable, easy-to-swallow and store, and as well support caregivers of children below 5 years on ART to enhance adherence and ensure virological suppression.

The hazard of HIV viral non-suppression was 1.73 times greater among patients with poor adherence compared to those with good adherence. Several other studies have also found an association between poor adherence to ART and non-viral load suppression.^12,26–28 Children depend on caregivers for support, including attending clinic visits and collecting medications, which may be challenging when caregivers are busy or face transport barriers. This highlights the need for continuous adherence monitoring and counselling in children and adolescents living with HIV.

Consistent with previous literature,^9,26,29 advanced WHO clinical stage (stages III and IV) was associated with viral non-suppression. Buju et al.²⁷ in the Democratic Republic of Congo reported that patients in advanced stage of the disease (stages III and IV) were more likely to experience viral non-suppression. Nabukeera et al in Uganda also revealed that children who were at WHO clinical stage 4 at ART initiation were more likely to have viral non suppression. Biological factors including severe illness, reduced immunity and other underlying disorders, coupled with psychological factors could have contributed to viral load non-suppression among patients in advanced WHO clinical stages.²⁶

This study also showed that non-disclosure was a predictor for HIV viral non-suppression. Similar findings have been reported in other studies.^27,30,31 Non-disclosure leads to reduced treatment engagement hindering adherence to ART, which can result in VL non-suppression.³² This finding emphasizes the importance of status disclosure for effective management of HIV among children and adolescents.

Having economic challenges was associated with HIV viral non-suppression. This finding is consistent with previous studies that showed household economic instability is associated with adverse HIV treatment outcomes including poor ART adherence and viral non-suppression.^33,34 Limited financial resources can make it difficult for patients to regularly attend clinic appointments which can lead to poor ART adherence and HIV viral non-suppression.

This study utilized data from all public health facilities that provide ART services in Gulu City; thus, these findings may be generalizable to routine healthcare of children and adolescents living with HIV in the country. Due to the retrospective nature of this study, we had no control of the data quality. Missing data in some files was also a challenge. Further, this study couldn’t ascertain the outcomes of the participants who were loss to follow-up/ transferred out, which could potentially understate the outcome estimates. However, during the analysis, these cases were treated as censored data. Future research could explore interventions to promote ART adherence among CAWH. Furthermore, a large, adequately powered prospective study in this region or similar settings is necessary to better understand determinants of treatment failure and inform targeted interventions.

Conclusion

HIV viral non-suppression among CAWH was high. Age less than 5 years, poor adherence to ART, non-disclosure of HIV status, advanced WHO clinical stage, and having economic challenges were associated viral non-suppression. We recommend intensified monitoring and adherence counselling, including identifying viral load focal persons identify and actively follow up non-suppressed CAWH, as well as strengthening patient and caregiver education on the importance of achieving and maintaining viral suppression. Persons with non-suppressed viral load should be screened closely for advanced HIV disease.

Supplemental Material

sj-docx-1-tai-10.1177_20499361261448464 – Supplemental material for Factors associated with HIV RNA viral non-suppression among children and adolescents with HIV attending public health facilities in Gulu City, Uganda: a retrospective cohort study

Supplemental material, sj-docx-1-tai-10.1177_20499361261448464 for Factors associated with HIV RNA viral non-suppression among children and adolescents with HIV attending public health facilities in Gulu City, Uganda: a retrospective cohort study by Ventrina Lanyero, Felix Bongomin, Daniel S. Ebbs, Ritah Nantale and Emmanuel Ochola in Therapeutic Advances in Infectious Disease

Footnotes

Acknowledgements

The authors acknowledge the administration of Gulu City and the research assistants.

Declarations

ORCID iD

Felix Bongomin

Supplemental material

Supplemental material for this article is available online.

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